High-resolution genome-wide in vivo footprinting of diverse transcription factors in human cells (Dnase-seq)
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE25344 | GEO | 2010/11/18
REPOSITORIES: GEO
Similar Datasets
Project description:Using DNaseI hypersensitivity (HS) assays (Dnase-seq), high resolution DNaseI digestion profiles were generated genome-wide in diverse human cell types. We showed that within general regions of DNaseI HS that are known to identify locations of gene regulatory elements, DNaseI digestion patterns allowed us to identify locations of individual transcription factor binding sites that protected against the bound DNA against digestion. To measure the accuracy of these footprints, we also generated ChIP-seq data for the CTCF DNA binding factor in the same cell growths. We found that DNaseI footprints containing the CTCF canonical binding motif show significant ChIP-seq signal while CTCF binding motifs not in footprints show almost no signal providing one measure of valdation of the DNaseI footprints. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf
2010-11-18 | GSE25416 | GEO
Project description:Using DNaseI hypersensitivity (HS) assays (Dnase-seq), high resolution DNaseI digestion profiles were generated genome-wide in diverse human cell types. We showed that within general regions of DNaseI HS that are known to identify locations of gene regulatory elements, DNaseI digestion patterns allowed us to identify locations of individual transcription factor binding sites that protected against the bound DNA against digestion. To measure the accuracy of these footprints, we also generated ChIP-seq data for the CTCF DNA binding factor in the same cell growths. We found that DNaseI footprints containing the CTCF canonical binding motif show significant ChIP-seq signal while CTCF binding motifs not in footprints show almost no signal providing one measure of valdation of the DNaseI footprints. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Five cell lines representing cervica carcinoma, chronic myeloid leukemia, embryonic stem cells, epidermal keratinocytes, and umbilical vein endothelial cells were analyzed using ChIP-seq.
2010-11-18 | E-GEOD-25416 | biostudies-arrayexpress
Project description:Using DNaseI hypersensitivity (HS) assays (Dnase-seq), high resolution DNaseI digestion profiles were generated genome-wide in diverse human cell types. We showed that within general regions of DNaseI HS that are known to identify locations of gene regulatory elements, DNaseI digestion patterns allowed us to identify locations of individual transcription factor binding sites that protected against the bound DNA against digestion. To measure the accuracy of these footprints, we also generated ChIP-seq data for the CTCF DNA binding factor in the same cell growths. We found that DNaseI footprints containing the CTCF canonical binding motif show significant ChIP-seq signal while CTCF binding motifs not in footprints show almost no signal providing one measure of valdation of the DNaseI footprints. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Six cell lines representing cervica carcinoma, chronic myeloid leukemia, human embryonic stem cells, lymphoblastoid cells, human epidermal keratinocytes and umbilical vein endothelial cells were analyzed using Dnase-seq.
2010-11-18 | E-GEOD-25344 | biostudies-arrayexpress
Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Richard Sandstrom mailto:sull@u.washington.edu). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). This track, produced as part of the mouse ENCODE Project, contains deep sequencing DNase data that will be used to identify sites where regulatory factors bind to the genome (footprints). Footprinting is a technique used to define the DNA sequences that interact with and bind DNA-binding proteins, such as transcription factors, zinc-finger proteins, hormone-receptor complexes, and other chromatin-modulating factors like CTCF. The technique depends upon the strength and tight nature of protein-DNA interactions. In their native chromatin state, DNA sequences that interact directly with DNA-binding proteins are relatively protected from DNA degrading endonucleases, while the exposed/unbound portions are readily degraded by such endonucleases. A massively parallel next-generation sequencing technique to define the DNase hypersensitive sites in the genome was adopted. The DNase samples were sequenced using next-generation sequencing machines to significantly higher depths of 300-fold or greater. This produces a base-pair level resolution of the DNase susceptibility maps of the native chromatin state. These base-pair resolution maps represent and are dependent upon the nature and the specificity of interaction of the DNA with the regulatory/modulatory proteins binding at specific loci in the genome; thus they represent the native chromatin state of the genome under investigation. The deep sequencing approach has been used to define the footprint landscape of the genome by identifying DNA motifs that interact with known or novel DNA binding proteins. Cells were grown according to the approved ENCODE cell culture protocols (http://hgwdev.cse.ucsc.edu/ENCODE/protocols/cell/mouse). Digital DNaseI was performed by DNaseI digestion of intact nuclei, followed by isolating DNaseI "double-hit" fragments (Sabo et al., 2006), and direct sequencing of fragment ends (which correspond to in vivo DNaseI cleavage sites) using the Solexa platform (27 bp reads). High-quality reads were mapped to the NCBI37/mm9 mouse genome using Bowtie 0.12.5; only unique mappings were kept. DNaseI sensitivity is directly reflected in raw tag density (Raw Signal), which is shown in the track as density of tags mapping within a 150 bp sliding window (at a 20 bp step across the genome). DNaseI hypersensitive zones (HotSpots) were identified using the HotSpot algorithm (Sabo et al., 2004). False discovery rate thresholds of 1.0% (FDR 0.01) were computed for each cell type by applying the HotSpot algorithm to an equivalent number of random uniquely mapping 36-mers. DNaseI hypersensitive sites (DHSs or Peaks) were identified as signal peaks within 1.0% (FDR 0.01) hypersensitive zones using a peak-finding algorithm. Only DNase Solexa libraries from unique cell types producing the highest quality data, as defined by Percent Tags in Hotspots (PTIH ~40%), were designated for deep sequencing to a depth of over 200 million tags. Results were validated by conventional DNaseI hypersensitivity assays using end-labeling/Southern blotting methods.
2012-09-19 | E-GEOD-40869 | biostudies-arrayexpress
Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Richard Sandstrom mailto:sull@u.washington.edu). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). This track, produced as part of the ENCODE Project, contains deep sequencing DNase data that will be used to identify sites where regulatory factors bind to the genome (footprints). Footprinting is a technique used to define the DNA sequences that interact with and bind DNA-binding proteins, such as transcription factors, zinc-finger proteins, hormone-receptor complexes, and other chromatin-modulating factors like CTCF. The technique depends upon the strength and tight nature of protein-DNA interactions. In their native chromatin state, DNA sequences that interact directly with DNA-binding proteins are relatively protected from DNA degrading endonucleases, while the exposed/unbound portions are readily degraded by such endonucleases. A massively parallel next-generation sequencing technique to define the DNase hypersensitive sites in the genome was adopted. Sequencing these next-generation-sequencing DNase samples to significantly higher depths of 300-fold or greater produces a base-pair level resolution of the DNase susceptibility maps of the native chromatin state. These base-pair resolution maps represent and are dependent upon the nature and the specificity of interaction of the DNA with the regulatory/modulatory proteins binding at specific loci in the genome; thus they represent the native chromatin state of the genome under investigation. The deep sequencing approach has been used to define the footprint landscape of the genome by identifying DNA motifs that interact with known or novel DNA binding proteins. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Cells were grown according to the approved ENCODE cell culture protocols. Digital DNaseI was performed by DNaseI digestion of intact nuclei, followed by isolating DNaseI 'double-hit' fragments as described in Sabo et al. (2006), and direct sequencing of fragment ends (which correspond to in vivo DNaseI cleavage sites) using the Solexa platform (27 bp reads). High-quality reads were mapped to the GRCh37/hg19 human genome using Bowtie 0.12.5 (Eland was used to map to NCBI36/hg18); only unique mappings were kept. DNaseI sensitivity is directly reflected in raw tag density (Signal), which is shown in the track as density of tags mapping within a 150 bp sliding window (at a 20 bp step across the genome). DNaseI hypersensitive zones (HotSpots) were identified using the HotSpot algorithm described in Sabo et al. (2004). False discovery rate thresholds of 1.0% (FDR 0.01) were computed for each cell type by applying the HotSpot algorithm to an equivalent number of random uniquely mapping 36-mers. DNaseI hypersensitive sites (DHSs or Peaks) were identified as signal peaks within 1.0% (FDR 0.01) hypersensitive zones using a peak-finding algorithm. Only DNase Solexa libraries from unique cell types producing the highest quality data, as defined by Percent Tags in Hotspots (PTIH ~40%) were designated for deep sequencing to a depth of over 200 million tags.
2010-12-29 | E-GEOD-26328 | biostudies-arrayexpress
Project description:We performed a meta analysis of publicly available TET1, 5mC, 5hmC and genome wide bisulfite profiling data mostly from mouse embryonic stem cells (ESC). Genome wide chromatin immunoprecipitation combined with deep sequencing (ChIP-seq) has revealed binding of the TET1 protein at CpG-island (CGI) promoters and at bivalent promoters. We show that TET1 also coincides with DNAseI hypersensitive sites (HS). Presence of TET1 at these THREE locations suggests that it may play a dual role: an active role at CpG-islands and DNAseI hypersensitive sites and a repressive role at bivalent loci. In line with the presence of TET1, significant enrichment of 5hmC but not 5mC is detected at bivalent promoters and DNaseI HS. Surprisingly, 5hmC is not detected or present at very low levels at CGI promoters notwithstanding the presence of TET1 at these loci. Our meta analysis suggest that asymmetric methylation is present at CA- and CT-repeats in the genome of some human ESC.
2011-11-24 | GSE31343 | GEO
Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Yijun Ruan mailto:ruanyj@gis.a-star.edu.sg). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). This track, produced as part of the ENCODE Project, contains deep sequencing DNase data that will be used to identify sites where regulatory factors bind to the genome (footprints). Footprinting is a technique used to define the DNA sequences that interact with and bind DNA-binding proteins, such as transcription factors, zinc-finger proteins, hormone-receptor complexes, and other chromatin-modulating factors like CTCF. The technique depends upon the strength and tight nature of protein-DNA interactions. In their native chromatin state, DNA sequences that interact directly with DNA-binding proteins are relatively protected from DNA degrading endonucleases, while the exposed/unbound portions are readily degraded by such endonucleases. A massively parallel next-generation sequencing technique to define the DNase hypersensitive sites in the genome was adopted. Sequencing these next-generation-sequencing DNase samples to significantly higher depths of 300-fold or greater produces a base-pair level resolution of the DNase susceptibility maps of the native chromatin state. These base-pair resolution maps represent and are dependent upon the nature and the specificity of interaction of the DNA with the regulatory/modulatory proteins binding at specific loci in the genome; thus they represent the native chromatin state of the genome under investigation. The deep sequencing approach has been used to define the footprint landscape of the genome by identifying DNA motifs that interact with known or novel DNA binding proteins. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Cells were grown according to the approved ENCODE cell culture protocols. Digital DNaseI was performed by DNaseI digestion of intact nuclei, followed by isolating DNaseI 'double-hit' fragments as described in Sabo et al. (2006), and direct sequencing of fragment ends (which correspond to in vivo DNaseI cleavage sites) using the Solexa platform (27 bp reads). High-quality reads were mapped to the GRCh37/hg19 human genome using Bowtie 0.12.5 (Eland was used to map to NCBI36/hg18); only unique mappings were kept. DNaseI sensitivity is directly reflected in raw tag density (Signal), which is shown in the track as density of tags mapping within a 150 bp sliding window (at a 20 bp step across the genome). DNaseI hypersensitive zones (HotSpots) were identified using the HotSpot algorithm described in Sabo et al. (2004). False discovery rate thresholds of 1.0% (FDR 0.01) were computed for each cell type by applying the HotSpot algorithm to an equivalent number of random uniquely mapping 36-mers. DNaseI hypersensitive sites (DHSs or Peaks) were identified as signal peaks within 1.0% (FDR 0.01) hypersensitive zones using a peak-finding algorithm. Only DNase Solexa libraries from unique cell types producing the highest quality data, as defined by Percent Tags in Hotspots (PTIH ~40%) were designated for deep sequencing to a depth of over 200 million tags.
2011-04-27 | E-GEOD-28867 | biostudies-arrayexpress
Project description:These tracks display a synthesis of evidence from different assays as part of the four Open Chromatin track sets. This track displays open chromatin regions and/or transcription factor binding sites identified in multiple cell types by one or more complementary methodologies, DNaseI hypersensitivity (HS) (Duke DNaseI HS), Formaldehyde-Assisted Isolation of Regulatory Elements (FAIRE) (UNC FAIRE), and chromatin immunoprecipitation (ChIP) for select regulatory factors (UTA TFBS). Each methodology was performed on the same cell type using identical growth conditions. (Note: Data for some or all ChIP experiments may not be available for all cell types). Regions that overlap between methodologies identify regulatory elements that are cross-validated indicating high confidence regions. In addition, multiple lines of evidence suggest that regions detected by a single assay (e.g., DNase-only or FAIRE-only) are also biologically relevant (Song et al., submitted). DNaseI HS data: DNaseI is an enzyme that has long been used to map general chromatin accessibility, and DNaseI "hypersensitivity" is a feature of active cis-regulatory sequences.The use of this method has led to the discovery of functional regulatory elements that include promoters, enhancers, silencers, insulators, locus control regions, and novel elements. DNaseI hypersensitivity signifies chromatin accessibility following binding of trans-acting factors in place of a canonical nucleosome. FAIRE data: FAIRE (Formaldehyde Assisted Isolation of Regulatory Elements) is a method to isolate and identify nucleosome-depleted regions of the genome. FAIRE was initially discovered in yeast and subsequently shown to identify active regulatory elements in human cells (Giresi et al., 2007). Similar to DNaseI HS, FAIRE appears to identify functional regulatory elements that include promoters, enhancers, silencers, insulators, locus control regions and novel elements. ChIP data: ChIP (Chromatin Immunoprecipitation) is a method to identify the specific location of proteins that are directly or indirectly bound to genomic DNA. By identifying the binding location of sequence-specific transcription factors, general transcription machinery components, and chromatin factors, ChIP can help in the functional annotation of the open chromatin regions identified by DNaseI HS mapping and FAIRE. Input data: As a background control experiment, we sequenced the input genomic DNA sample that was used for ChIP. Crosslinked chromatin is sheared and the crosslinks are reversed without carrying out the immunoprecipitation step. This sample is otherwise processed in a manner identical to the ChIP sample as described below. The input track is useful in revealing potential artifacts arising from the sequence alignment process such as copy number differences between the reference genome and the sequenced samples, as well as regions of poor sequence alignability. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf For each site, the maximum F-Seq Density Signal value has been calculated for each assay that was performed in that cell type. F-Seq employs Parzen kernel density estimation to create base pair scores (Boyle et al., 2008b). Significant regions, or peaks, were determined by fitting the data to a gamma distribution to calculate p-values. Contiguous regions where p-values were below a 0.05 (DNaseI HS, ChIP) or 0.1 (FAIRE) threshold were considered significant. See assay specific description pages ( Duke DNaseI HS, UNC FAIRE and UTA TFBS) for more details. A Fisher's Combined P-value for DNaseI HS and FAIRE was calculated using Fisher's combined probability test. First, a test statistic is calculated using the formula x^2 = -2*sum(ln(pi)) where pi are the p-values calculated for DNaseI HS and FAIRE. X2 follows a chi-squared distribution, thus a combined p-value can be assigned to this test statistic.
2012-09-12 | E-GEOD-40833 | biostudies-arrayexpress
Project description:Mammalian embryonic stem (ES) cells and sperm exhibit unusual chromatin packaging that plays important roles in cellular function. Here, we extend a recently developed technique, based on deep paired-end sequencing of lightly digested chromatin, to assess footprints of nucleosomes and other DNA-binding proteins genome-wide in murine ES cells and sperm. In ES cells, we recover well-characterized features of chromatin such as promoter nucleosome depletion, and further identify widespread footprints of sequence-specific DNA-binding proteins such as CTCF, which we validate in knockdown studies. We document global differences in nuclease accessibility between ES cells and sperm, finding that the majority of histone retention in sperm preferentially occurs in large gene-poor genomic regions, with only a small subset of nucleosomes being retained over promoters of developmental regulators. Finally, we describe evidence that CTCF remains associated with the genome in mature sperm, where it could play a role in organizing the sperm genome. We use Micrococcal Nuclease (MNase) to map chromatin structure in mouse ES cells and sperm. Specifically, we generate paired-end deep-sequencing libraries that are able to distinguish DNA digestion products by size, thus allowing us to simultaneously map nucleosomes as well as other DNA-binding proteins such as transcription factors.
2014-07-08 | E-GEOD-58101 | biostudies-arrayexpress
Project description:We performed a meta analysis of publicly available TET1, 5mC, 5hmC and genome wide bisulfite profiling data mostly from mouse embryonic stem cells (ESC). Genome wide chromatin immunoprecipitation combined with deep sequencing (ChIP-seq) has revealed binding of the TET1 protein at CpG-island (CGI) promoters and at bivalent promoters. We show that TET1 also coincides with DNAseI hypersensitive sites (HS). Presence of TET1 at these THREE locations suggests that it may play a dual role: an active role at CpG-islands and DNAseI hypersensitive sites and a repressive role at bivalent loci. In line with the presence of TET1, significant enrichment of 5hmC but not 5mC is detected at bivalent promoters and DNaseI HS. Surprisingly, 5hmC is not detected or present at very low levels at CGI promoters notwithstanding the presence of TET1 at these loci. Our meta analysis suggest that asymmetric methylation is present at CA- and CT-repeats in the genome of some human ESC. Examination of the distribution of 5-methylcytosine and 5-hydroxymethylcytosine in the genome of mouse embryonic stem cells.
2011-11-24 | E-GEOD-31343 | biostudies-arrayexpress